SPGAO: a simulation platform for genetic algorithm based on OOP

Abstract

The genetic algorithm is one of the most important intelligent method in the evolutionary algorithm and it has been applied in science and engineering field widely. In order to use the genetic algorithm easily and flexibly, this paper provides a simulation platform for the genetic algorithm by using the OOP language and the platform is called SPGAO. The architecture of SPGAO is presented and each module is implemented in detail. The data structure and functions for manipulating the genetic algorithm are defined in this platform and the chromosome data type, crossover, mutation, selection operators are defined. The animation demonstration module in SPGAO is implemented using the double buffer mechanism and it can show the progress of the every step of algorithm. The multithread technology is made for the genetic algorithm. Finally an example of function optimization based on genetic algorithm in SPGAO is provided and it shows that the platform make the user to use the genetic algorithm quickly and efficiently. The SPGAO provides strong interaction and better flexibility.